OCP-Based Nonlinear Model Predictive Control for Quadrotor Trajectory Tracking
Abstract
Fast online optimization is essential for nonlinear model predictive control (NMPC) on resource-limited aerial platforms. This paper presents an analytical-derivative NMPC solver for quadrotor trajectory tracking. For the state-affine translational model with held thrust and attitude commands, fourth-order Runge--Kutta integration yields an exact discrete-time prediction map. Forward--backward difference equations provide the gradient and exact Hessian of the finite-horizon cost condensed over the input sequence. These derivatives drive a nested optimal-control-based direction recursion, while a shifted warm start reuses the preceding solution. The resulting solver addresses the unconstrained tracking problem without a general-purpose nonlinear programming package. Gazebo experiments show comparable tracking accuracy to iLQR and two acados SQP configurations, with mean solver-time speedups of $1.97−−2.30$. In onboard flight tests, the mean solver time is $0.3121$\,ms, corresponding to speedups of $3.37−−5.77$ over the same baselines. The largest measured solver time is $3.7754$\,ms within a $20$-ms control period. These measurements cover the numerical solver and exclude estimation, communication, and command publication.
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BibTeX
@misc{shichao2026ocpbased,
title = {{OCP-Based Nonlinear Model Predictive Control for Quadrotor Trajectory Tracking}},
author = {Lv Shichao and Lv Chuanzhi and Wang Hongxia and Huanshui Zhang},
howpublished = {arXiv},
year = {2026},
month = nov,
doi = {10.48550/arxiv.2611.01628},
eprint = {2611.01628},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2611.01628},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - OCP-Based Nonlinear Model Predictive Control for Quadrotor Trajectory Tracking
AU - Lv Shichao
AU - Lv Chuanzhi
AU - Wang Hongxia
AU - Huanshui Zhang
PY - 2026
DA - 2026/11/01
PB - arXiv
DO - 10.48550/arxiv.2611.01628
UR - https://arxiv.org/abs/2611.01628
AB - Fast online optimization is essential for nonlinear model predictive control (NMPC) on resource-limited aerial platforms. This paper presents an analytical-derivative NMPC solver for quadrotor trajectory tracking. For the state-affine translational model with held thrust and attitude commands, fourth-order Runge--Kutta integration yields an exact discrete-time prediction map. Forward--backward difference equations provide the gradient and exact Hessian of the finite-horizon cost condensed over the input sequence. These derivatives drive a nested optimal-control-based direction recursion, while a shifted warm start reuses the preceding solution. The resulting solver addresses the unconstrained tracking problem without a general-purpose nonlinear programming package. Gazebo experiments show comparable tracking accuracy to iLQR and two acados SQP configurations, with mean solver-time speedups of $1.97−−2.30$. In onboard flight tests, the mean solver time is $0.3121$\,ms, corresponding to speedups of $3.37−−5.77$ over the same baselines. The largest measured solver time is $3.7754$\,ms within a $20$-ms control period. These measurements cover the numerical solver and exclude estimation, communication, and command publication.
ER -